Evidence map›Paper›PMID 39997017›Full record

ReviewBiosensors2025

SERS-Active Micro/Nanomachines for Biosensing.

Chenbing Li, Wenqing Zhang, Kai Zheng, Jianhe Guo

Abstract readReview
In one paragraph

Review in Biosensors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Tumor Exposomics: A New Paradigm for Individualized Continuous Exposure Monitoring.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  3. SERS-Based Nano- and Microsystems Toward Biomedical Applications.Small (Weinheim an der Bergstrasse, Germany) · 2026
    Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Chenbing LiGuangdong Provincial Key Laboratory of Sensing Technology and Biomedical Instrument, School of Biomedical Engineering, Shenzhen Campus, Sun Yat-sen University, Shenzhen 518107, China.
Wenqing ZhangGuangdong Provincial Key Laboratory of Sensing Technology and Biomedical Instrument, School of Biomedical Engineering, Shenzhen Campus, Sun Yat-sen University, Shenzhen 518107, China.ORCID 0009-0002-2266-701X
Kai ZhengGuangdong Provincial Key Laboratory of Sensing Technology and Biomedical Instrument, School of Biomedical Engineering, Shenzhen Campus, Sun Yat-sen University, Shenzhen 518107, China.
Jianhe GuoGuangdong Provincial Key Laboratory of Sensing Technology and Biomedical Instrument, School of Biomedical Engineering, Shenzhen Campus, Sun Yat-sen University, Shenzhen 518107, China.ORCID 0000-0002-0486-5437

Funding

National Natural Science Foundation of China 22104157Shenzhen Science and Technology Program RCBS20210706092410027the Natural Science Foundation of Guangdong Province 2020A1515110774the Natural Science Foundation of Guangdong Province 2023A151511099
6 · The paper itself

Abstract

Surface-enhanced Raman spectroscopy (SERS) has emerged as a powerful noninvasive analytical technique with widespread applications in biochemical analysis and biomedical diagnostics. The need for highly sensitive, reproducible, and efficient detection of biomolecules in complex biological environments has driven significant advancements in SERS-based biosensing platforms. In this context, micro/nanomachines (MNMs) have garnered attention as versatile SERS-active substrates due to their unique structural and motional characteristics at the micro- and nanoscale. This review explores the advantages of integrating MNMs with SERS for biosensing, discussing recent technological advances, various propulsion strategies, and their potential in a range of analytical applications.

Indexed as

Biosensing TechniquesSpectrum Analysis, RamanHumansNanostructuresbiosensinglocalized detectionmicro/nanomachinesSERStarget capture

Identifiers

PMID39997017
PMCPMC11853185

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.